SKILLEMALL.ai
GitHub ↗ RU Sign in

CC detecting-anomalous-authentication-patterns

Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning models to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs. Activates for requests involving authentication anomaly detection, login behavior analysis, UEBA implementation, or suspicious sign-in investigation.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 7 143 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning models to identify impossible travel, credential…

As a process C 63/100 · Has gaps — weak spots: failures and branches, running it twice

AnalyzerAzureData and analyticstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
86/100
safety, quality, tests
Safety 60%
95
Quality 40%
72
Run on models
none yet
Process rating
C
63/100
Has gaps
Failures and branches w 10
0
Running it twice w 4
30
When it triggers w 12
50
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 5

✓ No critical or high findings

Medium and low: 5
  • low Risky intent intent-offensive-security SKILL.md:5
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    stuffing, brute force, password spraying, and compromised account behaviors across
  • low Risky intent intent-offensive-security SKILL.md:51
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
    name: 'Brute Force: Password Spraying'
    quoted
  • low Risky intent intent-offensive-security SKILL.md:74
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
    - Detecting brute force, password spraying, and credential stuffing attacks in real time
    detector
  • low Risky intent intent-offensive-security SKILL.md:76
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - Correlating authentication anomalies with threat intelligence for lateral movement detection
  • low Risky intent intent-offensive-security SKILL.md:277
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
    ### Step 3: Detect Brute Force and Password Spraying
    detector

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 7143 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "domain"
  • note frontmatter-key unknown frontmatter key "subdomain"
  • note frontmatter-key unknown frontmatter key "atlas_techniques"
  • note frontmatter-key unknown frontmatter key "nist_ai_rmf"
  • note frontmatter-key unknown frontmatter key "nist_csf"
  • note frontmatter-key unknown frontmatter key "mitre_attack"
  • note frontmatter-key unknown frontmatter key "mitre_f3"
  • note edit-residue the text marks something as outdated (lines 553): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 63/100

  • 0Failures and branches. Linear process with no failure handling
  • 30Running it twice. 2 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 7143 tokens
  • 100Steps. 26 steps
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 410: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 26 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.